Given the move toward online services taking place in a range of applications, including productivity applications and operating systems, tools for accurately attributing observed activity to the correct person are becoming increasingly important. Online services frequently rely on unique identifiers, such as internet protocol (IP) addresses or Web browser cookies, to tailor offerings to their users based on how the user is perceived to use online services at a specific computing device (machine). Usage may be determined based on search histories, application usage (e.g., gaming, word-processing tools), and so on.
Typically, usage is based on the assumption that each machine identifier maps to an individual user. However, shared machines are common. As such, determining what to offer based on usage on a specific machine can be challenging. In cases where there is a shared machine, the search histories of multiple users are interwoven and are assigned the same identifier, creating noisy signals for any online service attempting to determine how to personalize its advertising, search results, or other services, to the current user.